Two‐Stage Fuzzy Decomposition Constraints for Unit Commitment

ABSTRACT Unit commitment (UC) determines the schedule of generators to optimise a chosen objective such as cost minimisation or social welfare maximisation. The usual UC objectives comprise hourly energy costs and intertemporal‐natured startup and shutdown costs and are constrained by hourly and intertemporal constraints. Excluding intertemporal constraints and costs from UC decomposes it into a set of hourly commitments or single‐period UC (SUC) problems that may be solved separately. Taking the SUC solutions directly provides a schedule that is no worse than solving conventional UC directly, due to the removal of intertemporal objective elements and constraints, but the resulting schedule will likely be infeasible. We propose to augment the conventional UC MILP formulation with the set of SUC solutions using non‐binding fuzzy decomposition constraints (FDC), which results in the proposed FDC‐assisted UC MILP formulation. FDC reduces the search space for solving the conventional UC MILP formulation. The computational time for solving the proposed two‐stage method, comprising 24 SUC in Stage 1 and FDC‐assisted UC MILP formulation in Stage 2, is compared with the time to solve the conventional UC MILP formulation on the IEEE 118‐bus and Polish 2383‐bus systems. The results demonstrate that the proposed two‐stage FDC‐assisted approach provides significant computation time reductions of up to 84% and 82% for these systems.